Before going into a dive, let's understand what LLM-based applications are.
Examples of LLM-Based Applications
- ChatGPT (OpenAI) – Conversational AI for general-purpose Q&A.
- Google Gemini (Google) – AI assistant integrated into Google products.
- Meta AI (Meta) – Chatbot embedded in Facebook, Instagram, and WhatsApp.
- Microsoft Copilot – AI-powered assistant in Office 365 and Windows.
- GitHub Copilot (OpenAI + Microsoft) – AI pair programmer for developers.
LangChain is a framework used to create LLM-Based Applications
Why do we need LangChain?
Before LangChain, developers faced significant challenges in integrating LLMs into applications, managing prompts, handling state, and combining LLMs with external tools. LangChain solves these problems by providing a modular, standardized framework that simplifies the development of LLM-powered applications. It enables developers to focus on building innovative solutions rather than dealing with the complexities of working with LLMs.
LangChain simplifies every stage of the LLM-Based Applications lifecycle.